The broad objective is to develop an analysis strategy for heart expression data and use it to identify without any preconceived knowledge of disease-associated genes the key genes, their targets, and their regulatory pathway, and to validate these results in biological systems. Specific Aims are: I: Link hypertrophy associated genes to transcriptional regulatory networks. II: Optimize the strategy for application to other cardiac gene expression data sets. Health Relatedness: A better understanding of the function of a p300- driven network in vivo is essential to guiding drug development both in cancer and heart disease. The experimental design includes running microarrays on murine models of hypertrophy, generating and applying novel statistical approaches to microarray data to extract genes related to hypertrophy, generating mathematical representations to visualize global expression profiles in 3D, studying promoter organization in silico to identify complex regulatory elements, searching the eukaryotic promoter database for these complex elements to find co-regulated genes, validating the complex elements in vivo using ChIP assay, overlapping the network from microarrays and literature to promoter driven network to find unknown candidate genes. [unreadable] [unreadable]